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Facebook Updates Patent Filing: Real-Time Search In Social Network

Facebook updated a pending patent this week titled "Real Time Content Searching In Social Network" that the company's patent inventors initially filed in April.

The patent, filed with the U.S. Patent and Trademark Office, describes a real-time method for receiving, identifying and indexing a Facebook member's post.

The technology determines an identifier associated with the user, a post identifier associated with the post, and a term identifier associated with a term in the post. It then selects a piece of a user-term index associated with the user identifier from among a several partitions of the user-term index.

The content storage and retrieval system within the social network supports the social graph and the connections that members have to each other through indexes. These indexes are organized to tie to real-time content posts, so that photos, video or anything that may be stored by a social networking system gets organized by users.

At the time the query is processed, the Facebook member's connections are identified based on the profile of the person conducting the search. The patent details the connections between people and things posted on their Facebook page, which in turn are indexed to appear in searches under specific related terms.

"The search or search results may also be filtered to only show results related to a particular connection or group of connections," according to the description of the patent filing. "A real time search engine compiles the post identifiers from matching posts in the user-term index query and uses the post identifiers to access the forward index and obtain the storage locations in the object stores for the posts."

That's not all. Facebook also has launched research to better understand the behavior of members who share in their posts the details of personal events in their lives. Per a report in MIT Technology Review, the company is working on artificial intelligence known as deep learning that uses simulated networks of brain cells to process data. "Applying this method to data shared on Facebook could allow for novel features, and perhaps boost the company’s ad targeting," according to the report.



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